Body mass index is associated with clinical outcomes in idiopathic pulmonary fibrosis

Association between body mass index (BMI) and prognosis in patients with idiopathic pulmonary fibrosis (IPF) remains uncertain. We investigated the association between BMI and clinical outcomes in patients with IPF using national health claims data. The study included 11,826 patients with IPF and rare incurable disease exemption codes (mean age: 68.9 years, male: 73.8%) and available BMI data who visited medical institutions between January 2002 and December 2018. Multivariable Cox proportional hazard models were used to evaluate the association of BMI with all-cause mortality and hospitalization. Based on BMI, 3.1%, 32.8%, 27.8%, and 36.4% were classified as underweight, normal, overweight, and obese, respectively. Multivariable analysis showed independent associations of overweight (hazard ratio [HR] 0.856, 95% confidence interval [CI] 0.801–0.916) and underweight (HR 1.538, 95% CI 1.347–1.757) with mortality in patients with IPF. Similarly, overweight (HR 0.887, 95% CI 0.834–0.943) and underweight (HR 1.265, 95% CI 1.104–1.449) were also associated with hospitalization in patients with IPF in the multivariable analysis. Spline HR curve analysis adjusted for all covariates revealed a non-linear relationship between BMI and mortality in patients with IPF. Our data suggest that BMI is associated with clinical outcomes in patients with IPF.

long-term nursing insurance for the elderly, registration status for rare and incurable diseases, health check-ups, clinic visits, and treatment in South Korea.Survival data were collected from the Korean Statistical Information Service.BMI data were obtained from the biennial health screening programs provided by National Health Insurance Sharing Service for all Korean citizens aged > 20 years 18 .This study was approved by the Institutional Review Board of Asan Medical Center (no.S2021-1136), and informed consent was waived because of the retrospective design and use of de-identified health claims data.All methods were performed in accordance with the relevant guidelines and regulations.

Study population
Patients with IPF were identified using the diagnostic code (J84.1)from the Korean Standard Classification of Diseases, 7th edition, and the rare intractable diseases (RID) program (Supplementary Table S1).The RID program provides medical expense support for patients with rare and incurable diseases, and registration requires strict criteria set by the National Health Insurance (NHI).Diagnosis codes in RID are highly reliable, and studies using the RID registration database have been published [19][20][21] .The inclusion criteria for IPF in the RID program include confirmation of the usual interstitial pneumonia pattern on a surgical lung biopsy or chest computed tomography (CT) and the exclusion of other known causes of interstitial lung disease (ILD).
Patients who visited secondary or tertiary medical institutes between January 2002 and December 2018 with both KCD-7 (J84.1) and RID registration codes (V236) and underwent chest CT within 3 months from the index date (the first date assigned to J84.1 and V236 codes) were defined as having IPF.Among 15,000 eligible IPF patients with available BMI data within 1 year of index date, the following patients were excluded: patients who received the first IPF diagnostic code in 2018 (n = 2407; insufficient follow-up period) and those < 50 years of age (n = 767; low possibility of IPF diagnosis).Finally, 11,826 participants were included in this study (Fig. 1).

Definition
BMI was classified according to the Asia-Pacific obesity criteria 22 : underweight (< 18.5 kg/m 2 ), normal (18.5-22.9kg/m 2 ), overweight (23-24.9kg/m 2 ), and obese (≥ 25.0 kg/m 2 ).The follow-up periods were calculated from the index date until the occurrence of death or censoring (December 2018).Clinical outcomes included all-cause mortality and hospitalization (all-cause and respiratory); respiratory hospitalization was defined as hospital admissions with diagnoses of respiratory system diseases classified under KCD-7 J00-J99 in addition to the IPF code (Supplementary Table S1).We identified comorbidities as repeated visits with the same disease codes within a year from the index date.Treatment data such as the at least 1-month prescription of antifibrotics (pirfenidone) and corticosteroids (oral or injectable), household income (low income was defined as the bottom 30% of the National Health Insurance premium), and type of patient's residence (urban [Seoul and Metropolitan cities] or rural [other areas]) were collected.

Statistical analysis
Continuous data were presented as mean ± standard deviation, whereas categorical data were presented as numbers (percentages).Differences in variables were compared using the chi-square test or analysis of variance test.Survival analysis for mortality or hospitalization was conducted using Kaplan-Meier survival curves, and between-group differences were assessed using log-rank tests.The association between BMI and clinical outcomes was assessed using the Cox proportional hazards model.BMI was analyzed as both a continuous variable and a categorized variable by using quartiles: Q1 (BMI 12.9-22 kg/m 2 ), Q2 (BMI 22.1-23.9kg/m 2 ), Q3 (BMI 24.0-25.9kg/m 2 ), and Q4 (BMI 26.0-41.3kg/m 2 ).Multivariable analysis was performed after adjusting for preselected covariates, including clinical variables (age, sex, diagnosis year, Charlson comorbidity index, prescribed medication, and home oxygen use) and socioeconomic variables (type of insurance [National Health Insurance vs. medical aid], income [high vs. low], and regional type [urban vs. rural]).Moreover, after adjusting for these covariates, a spline curve HR was used to evaluate the possible non-linear relationships between BMI and clinical outcomes.On the basis of previous studies that used the National Health Insurance Sharing Service database 23,24 , the adjusted HR was calculated by using a BMI cutoff of 22.0 kg/m 2 as reference to represent the normal value.A two-tailed p-value of < 0.05 was considered statistically significant.All statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC, USA).

Baseline characteristics and outcomes
The mean age of all patients was 68.9 years, and 73.8% of the patients were male (Table 1).Among the patients, 362 (3.1%), 3875 (32.8%), 3282 (27.8%), and 4307 (36.4%) patients were classified as underweight, normal, overweight, and obese, respectively (Fig. 2).The underweight group was older, more likely to be female, less likely to be ever-smokers, had higher Charlson comorbidity index scores, and received less treatment (pirfenidone and corticosteroid) compared with the other groups (Table 1).Furthermore, the underweight group had a shorter time to death or hospitalization (all-cause and respiratory) than other groups (Table 2).
In the unadjusted Cox analysis, being underweight was associated with increased mortality risk, whereas being overweight or obese was associated with decreased mortality risk in patients with IPF compared with those having a normal weight.In the multivariable analysis, being underweight (HR 1.538; 95% CI 1.347-1.757)and overweight (HR 0.856; 95% CI 0.801-0.916)were independently associated with mortality (Table 3).BMI levels as continuous variables were also associated with a reduced risk of mortality in patients with IPF in both unadjusted analysis (HR 0.957; 95% CI 0.948-0.966)and multivariable analysis (HR 0.978; 95% CI 0.969-0.987)(Table 3).Stratifying BMI into quartiles revealed a decreased risk of IPF mortality in all quartiles compared to Q1 (reference; BMI 12.9-22 kg/m 2 ) in the multivariable analysis (Table 3).
In the spline HR curve adjusted by clinical and socioeconomic covariates, a non-linear relationship between BMI and mortality was observed in patients with IPF (Fig. 3B) (Supplementary Table S2).Those with BMI < 22.0 kg/m 2 had a significantly increased mortality risk, whereas those with a 22.0 < BMI ≤ 23.6 kg/m 2 had a decreased risk of mortality.For patients with a BMI > 23.6 kg/m 2 , the mortality risk did not differ from the reference (BMI 22.0 kg/m 2 ).
In the spline HR curve analysis using a BMI of 22.0 kg/m 2 as a reference, the risk of all-cause hospitalization increased at a BMI < 22.0 kg/m 2 but decreased at a BMI > 22.0 kg/m 2 (Fig. 4b) (Supplementary Table S3).The risk for respiratory hospitalization also tended to decrease at a BMI > 22.0 kg/m 2 , although this was not statistically significant.However, for a BMI < 22 kg/m 2 , the risk of respiratory hospitalization significantly increased at Table 3. Cox proportional hazards analysis for risk factors of mortality in patients with IPF.BMI was categorized into four groups on the basis of quartiles: Q1 (BMI 12.9-22 kg/m 2 ), Q2 (BMI 22.1-23.9kg/m 2 ), Q3 (BMI 24.0-25.9kg/m 2 ), and Q4 (BMI 26.0-41.3kg/m 2 ).A multivariable model was used that was adjusted for age, sex, diagnosis year, Charlson comorbidity index, medication use (steroid, pirfenidone), insurance type, residential type, and household income.IPF idiopathic pulmonary fibrosis, HR hazard ratio, CI confidence interval, BMI body mass index.www.nature.com/scientificreports/ a BMI of 18.4 kg/m 2 (HR 1.312; 95% CI 1.150-1.497),but it showed an insignificant association with other BMI values (Fig. 5B) (Supplementary Table S4).

Discussion
This large-scale, nationwide, population-based study investigated the association between BMI and the clinical outcomes of IPF by using the claims database.We found that being underweight was associated with increased risk of mortality and hospitalization, whereas obesity and overweight were inversely associated with increased risk of mortality and hospitalization.Spline curve analysis revealed the non-linear association between BMI and prognosis.Specifically, a BMI below 22.0 kg/m 2 was associated with an increased risk of death or hospitalization, whereas a BMI above 22.0 kg/m 2 was associated with a decreased risk of these outcomes in patients with IPF.
Our study showed that a lower BMI was associated with worse prognosis, whereas a higher BMI was associated with better prognosis in patients with IPF.This is in line with previous studies that have shown increased mortality risk in patients with IPF who have lower BMI 6,7,[14][15][16] .In a retrospective IPF cohort (n = 197), Alakhras  et al. showed that a lower BMI was associated with increased mortality (HR 0.86; 95% CI 0.79-0.94) in a multivariable Cox analysis adjusted for gender, biopsy-confirmed diagnosis, forced vital capacity, diffusing capacity for carbon monoxide, and minimum oxygen saturation during exercise test 6 .Wright et al. studied 104 patients with IPF and found that a BMI ≤ 25.0 kg/m 2 was independently associated with increased risk of 12-month mortality (odds ratio [OR] 3.3; 95% CI 1.44-7.59) in the multivariable logistic analysis adjusted for carbon monoxide and home oxygen use 15 .Awano et al. used the Japanese Diagnosis Procedure Combination database to analyze patients with IPF who experienced acute exacerbation (AE) (n = 14,783) and found that patients who were underweight (< 18.5 kg/m 2 ) or obese (30.0 kg/m 2 ) had increased (OR 1.25; 95% CI 1.10-1.42)or decreased (OR 0.71; 95% CI 0.54-0.84)risk of in-hospital mortality, respectively, in a multivariable logistic analysis 8 .Similar results were found in patients with ILD 14 .In a multicenter study of patients with ILD (n = 1786; IPF = 34%), Comes et al. reported that a higher BMI was associated with decreased risk of 1-year mortality (HR 0.93; 95% CI 0.90-0.97) in a multivariable Cox analysis adjusted for the ILD-gender, age, and physiology index 14 .These collective findings further support the importance of BMI as a prognostic factor in IPF.
In this study, being underweight was an independent risk factor for poor clinical outcomes.Although the underlying mechanisms of this effect are not fully understood, patients with advanced chronic diseases often experience unintended weight loss because of loss of appetite, mental illness, or hormonal changes.Previous studies have also suggested that hormones involved in body weight regulation, such as leptin and adiponectin, may be association with the progression of fibrosis [25][26][27] .Adiponectin, one of the adipokines derived from adipocytes, is negatively correlated with BMI in patients with IPF 25 and has been shown to stimulate collagen production 26 and the differentiation of monocytes into fibroblasts 27 .These findings suggest that increased adiponectin in underweight patients with IPF may contribute to the progression of IPF.In the general population, obesity and being overweight are associated with increased mortality risk, possibly, because of immune system dysfunction 28 , disruption of lung physiology 29 , and predisposed comorbidities 30 .However, in many chronic lung or cardiovascular diseases, a protective effect of adipose tissue, known as the "obesity paradox, " has been reported [31][32][33][34][35] .Moreover, obesity may offer a metabolic buffer that can be utilized in times of stress or illness, thus potentially leading to better outcomes 36 .In fact, the "obesity paradox" is particularly evident in older individuals and those with advanced stages of the disease 37,38 .In addition, obese individuals are more likely to have comorbidities 30 , which may lead to an earlier diagnosis of IPF because of increased medical visits.
Our study added to the existing literature by revealing a non-linear relationship between BMI and mortality in patients with IPF.Previous studies suggested an association between BMI and IPF mortality without investigating non-linear associations 6,13,14 .Mazen et al. studied 197 patients with IPF and found a significant association between BMI and mortality (HR 0.86; 95% CI 0.79-0.94) in a multivariable Cox analysis adjusted for clinical variables 6 .Comes et al. also reported a significant association between BMI and 1-year mortality (HR 0.93; 95% CI 0.90-0.97) in patients with ILD (n = 1786; IPF = 34%) in a multivariable Cox analysis adjusting for the ILD-gender, age, and physiology index 14 .By contrast, in this study, Cox proportional analysis for mortality showed that the HR of mortality was the lowest in Q2.Additionally, the spline HR curve analysis showed that the inverse relationship between BMI and mortality was insignificant above a certain point in BMI (23.6 kg/ m 2 ).These results suggest that maintaining BMI in the optimal range may be beneficial for improving prognosis in patients with IPF.
Our IPF cohort had a lower proportion of underweight individuals (3.1%) and a relatively higher proportion of overweight (27.8%) and obese individuals (36.4%) compared with the general population or patients with chronic obstructive pulmonary disease in South Korea.According to the 2022 Korea National Health and Nutrition Examination Survey for the general population (n = 6265), the percentages of underweight, normal, overweight, and obese individuals were 11.6%, 35.8%, 20.0% and 32.6%, respectively (https:// knhan es.kdca.go.kr/).In addition, an analysis of the Korean COPD Subtype Study cohort (n = 1462 aged 40 years or older) showed that 10.7% were underweight, 42.4% were normal weight, 21.4% were overweight and 25.5% were obese 39 .The lower prevalence of underweight and higher rates of overweight and obesity in IPF patients may be due to treatment effects such as steroids, reduced physical activity due to respiratory symptoms, or older age compared to the other population.
Our study has some limitations.First, given that this study was based on data from the claims database, we were unable to obtain sufficient information, such as lung function.Instead, we adjusted for other clinical variables that are known to affect the prognosis of IPF, including age, sex, Charlson comorbidity index, medication, and home oxygen use, in the multivariable analysis.Second, considering that we included participants who underwent general health check-ups to collect BMI data, individuals with more health concerns or specific socioeconomic status could be included 40 .However, it is worth noting that national health screening programs supported by the government typically attract a diverse range of participants, including those from low-income backgrounds.Third, we defined IPF cases by using IPF diagnostic codes; therefore, the accuracy of diagnosis in our study may be lower than that in other studies that used medical records.To reduce this limitation, both IPF and RID registration codes were used to define IPF cases in this study.Prospective studies are needed to confirm our results.Despite these limitations, our study demonstrated an association between BMI and prognosis in a large population, as well as a non-linear relationship in IPF.
Our results suggest that BMI is associated with clinical outcomes in patients with IPF.Further studies are needed to determine whether BMI derangement drives prognosis or simply reflects disease severity.

Figure 1 .
Figure 1.Flow diagram of the study population.IPF idiopathic pulmonary fibrosis, KCD-7 Korean Standard Classification of Diseases, 7th edition, RID rare intractable diseases, BMI body mass index.

Figure 3 .
Figure 3. Association between BMI and mortality in patients with IPF.(a) Comparison of Kaplan-Meier survival curves according to BMI categories in patients with IPF.(b) Spline curve analysis for mortality.The spline curve hazard ratio was calculated and adjusted for covariates such as age, sex, diagnosis year, Charlson comorbidity index, medication use (steroid and pirfenidone), insurance type, residential type, and household income.A reference BMI of 22.0 kg/m 2 was used for calculating the adjusted hazard ratio (vertical dotted line).

Figure 4 .
Figure 4. Association between BMI and all-cause hospitalization in patients with IPF.(a) Comparison of all-cause hospitalization-free survival curves according to BMI categories in patients with IPF.(b) Spline curve analysis for all-cause hospitalization.The spline curve hazard ratio was calculated and adjusted for covariates such as age, sex, diagnosis year, Charlson comorbidity index, medication use (steroid and pirfenidone), insurance type, residential type, and household income.A reference BMI of 22.0 kg/m 2 was used for calculating the adjusted HR (vertical dotted line).

Figure 5 .
Figure 5. Association between BMI and respiratory hospitalization in patients with IPF.(a) Comparison of respiratory hospitalization-free survival curves according to BMI categories in patients with IPF.(b) Spline curve analysis for respiratory hospitalization.The spline curve hazard ratio was calculated and adjusted for covariates such as age, sex, diagnosis year, Charlson comorbidity index, medication use (steroid and pirfenidone), insurance type, residential type, and household income.A reference BMI of 22.0 kg/m 2 was used for calculating the adjusted HR (vertical dotted line).

Table 1 .
Comparison of baseline characteristics of patients with IPF according to BMI.Data were presented as mean ± standard deviation or number with frequency.IPF idiopathic pulmonary fibrosis, BMI body mass index, NTM nontuberculous mycobacterial, COPD chronic obstructive lung disease, CCI Charlson comorbidity index.

Table 2 .
Comparison of clinical outcomes in patients with IPF according to BMI.Data were presented as mean ± standard deviation or median (interquartile range), unless otherwise indicated.IPF idiopathic pulmonary fibrosis, BMI body mass index, IQR interquartile range.*Data were presented as number (%).